128 research outputs found

    Understanding the Physics of Functional Fibers in the Gastrointestinal Tract: An Evidence-Based Approach to Resolving Enduring Misconceptions about Insoluble and Soluble Fiber

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    AbstractEnduring misconceptions about the physical effects of fiber in the gut have led to misunderstandings about the health benefits attributable to insoluble and soluble fiber. This review will focus on isolated functional fibers (eg, fiber supplements) whose effects on clinical outcomes have been readily assessed in well-controlled clinical studies. This review will also focus on three health benefits (cholesterol lowering, improved glycemic control, and normalizing stool form [constipation and diarrhea]) for which reproducible evidence of clinical efficacy has been published. In the small bowel, clinically meaningful health benefits (eg, cholesterol lowering and improved glycemic control) are highly correlated with the viscosity of soluble fibers: high viscosity fibers (eg, gel-forming fibers such as b-glucan, psyllium, and raw guar gum) exhibit a significant effect on cholesterol lowering and improved glycemic control, whereas nonviscous soluble fibers (eg, inulin, fructooligosaccharides, and wheat dextrin) and insoluble fibers (eg, wheat bran) do not provide these viscosity-dependent health benefits. In the large bowel, there are only two mechanisms that drive a laxative effect: large/coarse insoluble fiber particles (eg, wheat bran) mechanically irritate the gut mucosa stimulating water and mucous secretion, and the high water-holding capacity of gel-forming soluble fiber (eg, psyllium) resists dehydration. Both mechanisms require that the fiber resist fermentation and remain relatively intact throughout the large bowel (ie, the fiber must be present in stool), and both mechanisms lead to increased stool water content, resulting in bulky/soft/easy-to-pass stools. Soluble fermentable fibers (eg, inulin, fructooligosaccharide, and wheat dextrin) do not provide a laxative effect, and some fibers can be constipating (eg, wheat dextrin and fine/smooth insoluble wheat bran particles). When making recommendations for a fiber supplement, it is essential to recognize which fibers possess the physical characteristics required to provide a beneficial health effect, and which fiber supplements are supported by reproducible, rigorous evidence of one or more clinically meaningful health benefits

    Dietary Magnesium and Genetic Interactions in Diabetes and Related Risk Factors: A Brief Overview of Current Knowledge

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    Nutritional genomics has exploded in the last decade, yielding insights—both nutrigenomic and nutrigenetic—into the physiology of dietary interactions and our genes. Among these are insights into the regulation of magnesium transport and homeostasis and mechanisms underlying magnesium’s role in insulin and glucose handling. Recent observational evidence has attempted to examine some promising research avenues on interaction between genetics and dietary magnesium in relation to diabetes and diabetes risk factors. This brief review summarizes the recent evidence on dietary magnesium’s role in diabetes and related traits in the presence of underlying genetic risk, and discusses future potential research directions

    Using Machine Learning to Predict Obesity Based on Genome-Wide and Epigenome-Wide Gene-Gene and Gene-Diet Interactions.

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    Obesity is associated with many chronic diseases that impair healthy aging and is governed by genetic, epigenetic, and environmental factors and their complex interactions. This study aimed to develop a model that predicts an individual's risk of obesity by better characterizing these complex relations and interactions focusing on dietary factors. For this purpose, we conducted a combined genome-wide and epigenome-wide scan for body mass index (BMI) and up to three-way interactions among 402,793 single nucleotide polymorphisms (SNPs), 415,202 DNA methylation sites (DMSs), and 397 dietary and lifestyle factors using the generalized multifactor dimensionality reduction (GMDR) method. The training set consisted of 1,573 participants in exam 8 of the Framingham Offspring Study (FOS) cohort. After identifying genetic, epigenetic, and dietary factors that passed statistical significance, we applied machine learning (ML) algorithms to predict participants' obesity status in the test set, taken as a subset of independent samples (n = 394) from the same cohort. The quality and accuracy of prediction models were evaluated using the area under the receiver operating characteristic curve (ROC-AUC). GMDR identified 213 SNPs, 530 DMSs, and 49 dietary and lifestyle factors as significant predictors of obesity. Comparing several ML algorithms, we found that the stochastic gradient boosting model provided the best prediction accuracy for obesity with an overall accuracy of 70%, with ROC-AUC of 0.72 in test set samples. Top predictors of the best-fit model were 21 SNPs, 230 DMSs in genes such as CPT1A, ABCG1, SLC7A11, RNF145, and SREBF1, and 26 dietary factors, including processed meat, diet soda, French fries, high-fat dairy, artificial sweeteners, alcohol intake, and specific nutrients and food components, such as calcium and flavonols. In conclusion, we developed an integrated approach with ML to predict obesity using omics and dietary data. This extends our knowledge of the drivers of obesity, which can inform precision nutrition strategies for the prevention and treatment of obesity. Clinical Trial Registration: [www.ClinicalTrials.gov], the Framingham Heart Study (FHS), [NCT00005121].This research was funded by the United States Department of Agriculture (USDA), Agriculture Research Service (ARS) under agreement no. 8050-51000-107-000D. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the USDA. The USDA is an equal opportunity provider and employer. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the USDA.S

    Evaluating whole grain intervention study designs and reporting practices using evidence mapping methodology

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    Consumption of whole grains have been associated with reduced risk of chronic diseases in many observational studies; yet, results of intervention studies are mixed. We aimed to use evidence mapping to capture the methodological and reporting variability in whole grain intervention studies that may contribute to this inconsistency. We conducted a reproducible search in OVID Medline for whole grain human intervention studies (published 1946 to February 2018). After screening based on a priori criteria, we identified 202 publications describing a total of 213 unique trials. Over half (55%) were acute trials, lasting ≀1 day, 30% were moderate duration studies (up to 6 weeks) and 15% were of longer duration (more than 6 weeks). The majority of acute trials (75%) examined measures of glycaemia and/or insulinemia, while most of the longer trials included measures of cardiometabolic health (71%), appetite/satiety (57%) and weight/adiposity (56%). Among the moderate and long duration trials, there was a wide range of how whole grains were described but only 10 publications referenced an established definition. Only 55% of trials reported the actual amount of whole grains (in grams or servings), while 36% reported the amount of food/product and 9% did not report a dose at all. Of the interventions that provided a mixture of whole grains, less than half (46%) reported the distribution of the different grain types. Reporting of subject compliance also varied and only 22% used independent biomarkers of whole grain intake. This evidence map highlights the need to standardize both study protocols and reporting practices to support effective synthesis of study results and provide a stronger foundation to better inform nutrition scientists and public health policy

    Measurement of diets that are healthy, environmentally sustainable, affordable, and equitable: A scoping review of metrics, findings, and research gaps

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    IntroductionResearch on the impacts of dietary patterns on human and planetary health is a rapidly growing field. A wide range of metrics, datasets, and analytical techniques has been used to explore the role of dietary choices/constraints in driving greenhouse gas (GHG) emissions, environmental degradation, health and disease outcomes, and the affordability of food baskets. Many argue that each domain is important, but few have tackled all simultaneously in analyzing diet-outcome relationships.MethodsThis paper reviews studies published between January 2015 and December 2021 (inclusive) that examined dietary patterns in relation to at least two of the following four thematic pillars: (i) planetary health, including, climate change, environmental quality, and natural resource impacts, (ii) human health and disease, (iii) economic outcomes, including diet cost/affordability, and (iv) social outcomes, e.g., wages, working conditions, and culturally relevant diets. We systematically screened 2,425 publications by title and abstract and included data from 42 eligible publications in this review.ResultsMost dietary patterns used were statistically estimated or simulated rather than observed. A rising number of studies consider the cost/affordability of dietary scenarios in relation to optimized environmental and health outcomes. However, only six publications incorporate social sustainability outcomes, which represents an under-explored dimension of food system concerns.DiscussionThis review suggests a need for (i) transparency and clarity in datasets used and analytical methods; (ii) explicit integration of indicators and metrics linking social and economic issues to the commonly assessed diet-climate-planetary ecology relationships; (iii) inclusion of data and researchers from low- and middle-income countries; (iv) inclusion of processed food products to reflect the reality of consumer choices globally; and (v) attention to the implications of findings for policymakers. Better understanding is urgently needed on dietary impacts on all relevant human and planetary domains simultaneously

    Understanding communication pathways to foster community engagement for health improvement in North West Pakistan

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    Background: This paper describes the community engagement process undertaken to ascertain the focus, development and implementation of an intervention to improve iodised salt consumption in rural communities in North West Pakistan. The Jirga is a traditional informal structure, which gathers men respected within their community and acts in a governing and decision making capacity in the Pukhtoon culture. The Jirga system had a dual purpose for the study; to access men from the community to discuss the importance of iodised salt, and as an engagement process for the intervention. Methods: A number of qualitative data collection activities were undertaken, with Jirga members and their wives, male and female outreach workers and two groups of women, under and over forty years old. The aim of these were to highlight the communication channels and levers of influence on health behaviour, which were multiple and complex and all needed to be taken into consideration in order to ensure successful and locally sensitive community engagement. Results: Communication channels are described within local families and the communities around them. The key influential role of the Jirga is highlighted as linked both to the standing of its members and the community cohesion ethos that it embodies. Engaging Jirga members in discussions about iodised salt was key in designing an intervention that would activate the most influential levers to decision making in the community. Gendered decision making-processes within the household have been highlighted as restricting women’s autonomy. Whilst in one respect our data confirm this, a more complex hierarchy of decisional power has been highlighted, whereby the concept of ‘wisdom’, an amalgamation of age, experience and education, presents important possibilities. Community members with the least autonomy are the youngest uneducated females, who rely on a web of socially and culturally determined ways to influence decision-making. Conclusions: The major lines of communication and influence in the local community described are placed within the wider literature on community engagement in health improvement. The process of maximisation of local cultural knowledge as part of a community engagement effort is one that has application well beyond the particular setting of this study

    Sugar-sweetened beverage intake associations with fasting glucose and insulin concentrations are not modified by selected genetic variants in a ChREBP-FGF21 pathway : a meta-analysis

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    Aims/hypothesis Sugar-sweetened beverages (SSBs) are a major dietary contributor to fructose intake. A molecular pathway involving the carbohydrate responsive element-binding protein (ChREBP) and the metabolic hormone fibroblast growth factor 21 (FGF21) may influence sugar metabolism and, thereby, contribute to fructose-induced metabolic disease. We hypothesise that common variants in 11 genes involved in fructose metabolism and the ChREBP-FGF21 pathway may interact with SSB intake to exacerbate positive associations between higher SSB intake and glycaemic traits. Methods Data from 11 cohorts (six discovery and five replication) in the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided association and interaction results from 34,748 adults of European descent. SSB intake (soft drinks, fruit punches, lemonades or other fruit drinks) was derived from food-frequency questionnaires and food diaries. In fixed-effects meta-analyses, we quantified: (1) the associations between SSBs and glycaemic traits (fasting glucose and fasting insulin); and (2) the interactions between SSBs and 18 independent SNPs related to the ChREBP-FGF21 pathway. Results In our combined meta-analyses of discovery and replication cohorts, after adjustment for age, sex, energy intake, BMI and other dietary covariates, each additional serving of SSB intake was associated with higher fasting glucose (beta +/- SE 0.014 +/- 0.004 [mmol/l], p = 1.5 x 10(-3)) and higher fasting insulin (0.030 +/- 0.005 [log(e) pmol/l], p = 2.0 x 10(-10)). No significant interactions on glycaemic traits were observed between SSB intake and selected SNPs. While a suggestive interaction was observed in the discovery cohorts with a SNP (rs1542423) in the beta-Klotho (KLB) locus on fasting insulin (0.030 +/- 0.011 log(e) pmol/l, uncorrected p = 0.006), results in the replication cohorts and combined meta-analyses were non-significant. Conclusions/interpretation In this large meta-analysis, we observed that SSB intake was associated with higher fasting glucose and insulin. Although a suggestive interaction with a genetic variant in the ChREBP-FGF21 pathway was observed in the discovery cohorts, this observation was not confirmed in the replication analysis.Peer reviewe

    Heterozygous ANKRD17 loss-of-function variants cause a syndrome with intellectual disability, speech delay, and dysmorphism

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    ANKRD17 is an ankyrin repeat-containing protein thought to play a role in cell cycle progression, whose ortholog in Drosophila functions in the Hippo pathway as a co-factor of Yorkie. Here, we delineate a neurodevelopmental disorder caused by de novo heterozygous ANKRD17 variants. The mutational spectrum of this cohort of 34 individuals from 32 families is highly suggestive of haploinsufficiency as the underlying mechanism of disease, with 21 truncating or essential splice site variants, 9 missense variants, 1 in-frame insertion-deletion, and 1 microdeletion (1.16 Mb). Consequently, our data indicate that loss of ANKRD17 is likely the main cause of phenotypes previously associated with large multi-gene chromosomal aberrations of the 4q13.3 region. Protein modeling suggests that most of the missense variants disrupt the stability of the ankyrin repeats through alteration of core structural residues. The major phenotypic characteristic of our cohort is a variable degree of developmental delay/intellectual disability, particularly affecting speech, while additional features include growth failure, feeding difficulties, non-specific MRI abnormalities, epilepsy and/or abnormal EEG, predisposition to recurrent infections (mostly bacterial), ophthalmological abnormalities, gait/balance disturbance, and joint hypermobility. Moreover, many individuals shared similar dysmorphic facial features. Analysis of single-cell RNA-seq data from the developing human telencephalon indicated ANKRD17 expression at multiple stages of neurogenesis, adding further evidence to the assertion that damaging ANKRD17 variants cause a neurodevelopmental disorder
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